Applications that are implemented on devices operating in communications networks are becoming increasingly sophisticated as far as the functions and services that they offer to users. Examples of such applications include personal digital assistants and search engines that are able to process input queries in the form of speech or text and provide answers to questions or facilitate performance of relevant functions for the user of a device. The processing of input queries is done by functions that are able to perform natural language understanding (NLU) processing on the input queries and provide an intent determination so the application can function according to the user's desires. Several current major mobile device manufacturers and operating system (OS) providers include a personal digital assistant application that is integrated into the OS of their devices.
The NLU processing and intent determination for an application is typically mainly performed in a server system/infrastructure that is designed, constructed and maintained by the application provider. The design, construction and maintenance of a server system that provides quality NLU processing and intent determination requires a large amount of resources including experienced manpower, access to knowledge data bases, access to relevant data logs, including query and search histories, processing infrastructure, etc. An aspect of the performance of such a NLU processing and intent determination system that is widely used, for example, with a mobile device or computer operating system, is that the performance of the system benefits from a better quality and more robust system because of the availability of learning feedback loops with large amounts of data from user interactions with the system.
Device manufacturers/OS providers also have supported the increasingly and widespread use of applications created by third party developers on their devices. These third party applications provide a wide range of functions. The third party application developers are often smaller companies that cannot provide resources and processing infrastructure for enhanced NLU and intent understanding functionality.